In the next section we will discuss about how these parameters have been incorporated to implement SUI channel model for our simulation.

# 4.3.2 SUI channel models Implementation:

The goal of the model implementation is to simulate channel coefficients. Channel coefficients with the specified distribution and spectral power density are generated using the method of filtered noise [34]. A set of complex zeromean Gaussian distributed number is generated with a variance of 0.5 for the real and imaginary part for each tap to achieve the total average power of this distribution is 1. In this way, we get a Rayleigh distribution (equivalent to Rice with K=0) for the magnitude of the complex coefficients. In case of a Ricean distribution K>0), a constant path component m has to be added to the Rayleigh set of coefficients. TheKfactor specifies the ratio of powers between this constant part and the variable part. The distribution of the power is shown below:

total power P of each tap:

p = |m| ^{2 }+

2

(4.9)

where m is the complex constant and

2

the variance of the complex Gaussian set

the ratio of power is :

k

m^{2 }

2

(4.10)

From the above two equations, the power of the complex Gaussian:

1 ^{2 } p. _{k 1 }

(4.11)

and the power of the constant part as:

k m p. _{k 1 }2

(4.12)

The SUI channel model address a speci ic power spectral density (PSD) function for the scatter component channel coefficients which is given by:

39